Upload research_synthesis.py

metadata_search/research_synthesis.py

@@ -341,12 +341,12 @@ def register_research_synthesis_route(research_bp):
         # Optional research-only provider selection. Existing HF requests
         # remain the default and keep their original auto-routing behavior.
         provider = (_clean(body.get("provider")) or "hf").lower()
-        if provider not in {"hf", "azure"}:
-            return jsonify({"ok": False, "error": "provider must be hf or azure"}), 400
-        if provider == "azure":
+        if provider not in {"hf", "azure", "deepseek"}:
+            return jsonify({"ok": False, "error": "provider must be hf, azure or deepseek"}), 400
+        if provider in {"azure", "deepseek"}:
             if os.getenv("ENABLE_EXTERNAL_LLM", "false").lower() not in {"1", "true", "yes"}:
                 return jsonify({"ok": False, "error": "External LLM is disabled"}), 403
-            # A research-only secret is mandatory for paid Azure calls.
+            # A research-only secret is mandatory for paid external API calls.
             research_token = os.getenv("WATERSCOPE_RESEARCH_TOKEN", "").strip()
             supplied_token = request.headers.get("X-Research-Token", "").strip()
             if not research_token or not hmac.compare_digest(supplied_token, research_token):
@@ -357,7 +357,7 @@ def register_research_synthesis_route(research_bp):
             if application not in AGENT_APPLICATIONS:
                 return jsonify({
                     "ok": False,
-                    "error": "For Azure, specify an application: "
+                    "error": "For external LLMs, specify an application: "
                              + ", ".join(AGENT_APPLICATIONS),
                 }), 400
 
@@ -468,7 +468,7 @@ def register_research_synthesis_route(research_bp):
 
             model_start = time.perf_counter()
             external_result = None
-            if provider == "azure":
+            if provider in {"azure", "deepseek"}:
                 from llm_services.llm_client import run_application
                 # The same complete context, question and application prompt
                 # are passed to both model paths. HF's prefix_context() is
@@ -477,15 +477,17 @@ def register_research_synthesis_route(research_bp):
                     application=application,
                     context=model_context,
                     question=question_to_model,
-                    provider="azure",
-                    model=None,  # use AZURE_LLM_DEPLOYMENT, not HF selector
+                    provider=provider,
+                    model=(model if provider == "deepseek" else None),  # Azure uses AZURE_LLM_DEPLOYMENT
                     max_completion_tokens=max_new_tokens_requested,
                 )
                 answer = external_result["answer"]
                 strategy = f"waterscope:{application}"
                 diagnostics = {
-                    "provider": "azure",
+                    "provider": provider,
                     "model": external_result.get("model_returned"),
+                    "model_requested": external_result.get("model_requested"),
+                    "thinking_mode": external_result.get("thinking_mode"),
                     "finish_reason": external_result.get("finish_reason"),
                     "metering": external_result.get("metering"),
                     "prompt_version": external_result.get("prompt_version"),
@@ -526,6 +528,7 @@ def register_research_synthesis_route(research_bp):
                 "provider_used": provider,
                 "external_model": external_result.get("model_returned") if external_result else None,
                 "external_usage": external_result.get("metering") if external_result else None,
+                "thinking_mode": external_result.get("thinking_mode") if external_result else None,
                 "application_requested": application,
                 "application_used": application_used,
                 "model_requested": model or "",
@@ -578,7 +581,7 @@ def register_research_synthesis_route(research_bp):
                     "mcp" if chat_api.use_mcp() else "direct"
                 ),
                 "diagnostics": diagnostics,
-                "llm_backend": "azure" if provider == "azure" else chat_api.llm_backend_name(),
+                "llm_backend": provider if provider in {"azure", "deepseek"} else chat_api.llm_backend_name(),
                 "trace_status": {
                     "captured_full_context": bool(
                         full_context
@@ -607,7 +610,7 @@ def register_research_synthesis_route(research_bp):
                         MAX_RESEARCH_PAPERS
                     ),
                     "token_override_scope": (
-                        "external_api" if provider == "azure" else "isolated_function_clone"
+                        "external_api" if provider in {"azure", "deepseek"} else "isolated_function_clone"
                     ),
                 },
             }